Can Feeding a Millet-Based Diet Improve the Growth of Children?—A Systematic Review and Meta-Analysis

Undernutrition, such as stunting and underweight, is a major public health concern, which requires multi-sectoral attention. Diet plays a key role in growth and should optimally supply all required nutrients to support the growth. While millets (defined broadly to include sorghum) are traditional foods, and climate smart nutritious crops, which are grown across Africa and Asia, they have not been mainstreamed like rice, wheat, and maize. Diversifying staples with millets can potentially provide more macro and micro nutrients, compared to the mainstream crops. However, there is little known scientific evidence to prove millets’ efficacy on growth. Therefore, a systematic review and meta-analysis was conducted to collate evidence of the benefits of millets in improving the growth of children. Eight eligible randomized feeding trials were included in the meta-analysis. Results from the randomized effect model showed a significant effect (p < 0.05) of millet-based diets on mean height (+28.2%) (n = 8), weight (n = 9) (+26%), mid upper arm circumference (n = 5) (+39%) and chest circumference (n = 5) (+37%) in comparison to regular rice-based diets over for the period of 3 months to 4.5 years, which was based on largely substituting rice with millets. When an enhanced and diverse diet was served, replacing rice with millet had only minimal growth improvement on chest circumference (p < 0.05). The quality assessment using GRADE shows that the evidence used for this systematic review and meta-analysis had moderate quality, based on eight scoring criteria. These results demonstrate the value of adding millet as the staple for undernourished communities. Further understanding of the efficacy of millets on growth in a wider range of diets is important to develop appropriate dietary programs and improve the nutritional status of various age groups across Africa and Asia.

Anthropometric Measurements to Predict NICU Admission for Infants of Diabetic Mothers

Aim: Can NICU admission of IDM be predicted by anthropometric measurements like birth weight, lenght, head circumference (HC), mid upper arm circumference (MUAC) or triceps skin fold thickness (TSFT). Method: Eighty-six-term IDMs were analyzed prospectively. MUAC, HC and TSFT were measured within 48 hours of life. Prenatal-natal-postnatal problems; NICU admission; maternal characteristics, HbA1c were recorded. Results: Mean birth weight, gestational age were 3453.3±582.4g and 38.0±0.97weeks. 63.9% of IDMs was admitted to NICU. 56.3% hospitalized due respiratory problems; 32,7 % required endotracheal intubation. Mean MUAC, TSFT, HC and MUAC/HC ratio were 11.2±1.1 cm, 7.1±2.2 mm, 35.0±1.8 cm and 0.32±0.03 cm respectively for all. Although there was no significant relation between NICU admission and MUAC (p=0.071), TSFT and MUAC/HC were significantly higher in babies admitted to NICU (p=0.006 for TSFT, p<0.001 for MUAC/HC). HC was significantly low in babies followed in NICU (P<0.001). With increment of TSFT, MUAC/HC and HbA1c, NICU admission increases positively, but HC affects NICU admission negatively (OR for TSFT:1.6, OR for MUAC/HC: 2.1, OR for HbA1c: OR for HC:0,3). Mechanic ventilation requirement is affected positively by TSFT (p=0.008, OR:1.5) and affected negatively by HC (p=0.004, OR:0.6). Conclusion: This preliminary study showed; TSFT, HC and MUAC/HC ratio are helpful criterias to predict NICU admission risk for IDMs and might be helpful for risk assesment in limited settings. Bangladesh Journal of Medical Science Vol. 21(1) 2022 Page : 72-78

Malnutrition could predict 3-month functional prognosis in mild stroke patients: Findings from a Nationwide Stroke Registry

Background: Previous studies showed the inconsistent effects of malnutrition contributing to poor prognosis of stroke. The aim of this study is to explore the effect of malnutrition on 3-month functional prognosis of stroke patients with different stroke severity assessed by the national institute of health stroke scale (NIHSS). Patients with first-ever stroke were consecutively enrolled in a nationwide, multicenter, and prospective registry from March 2007 to January 2008. Methods: Nutritional status was assessed at admission. Malnutrition was defined by any abnormality of 6 nutrition indicators, including body mass index (BMI), mid-upper arm circumference (MUAC), triceps skinfold thickness (TSF), haemoglobin, albumin, and prealbumin. Stroke patients were classified into mild (NIHSS<8) and severe (NIHSS≥8) groups. Multivariable logistic regression was performed to assess the risk of poor functional prognosis [ modified Rankin Scale (mRS) ≥3] and mortality at 3-month follow-up in mild or severe patients with malnutrition at admission. A total of 755 patients with first-ever stroke were enrolled in the study. Results: Multivariable analysis showed that malnutrition independently contributed to a higher risk of mRS 3-6 at 3-month for mild stroke patients [odds ratio (OR) 1.86, 95% confidence interval (CI) 1.04-3.34], but didn’t for severe stroke patients (OR 0.91, 95% CI 0.53-1.54) after adjusting for confounders including age, NIHSS, and infection et al. After adjusting for the potential confounders, malnutrition was still an independent risk factor for 3-month poor functional prognosis in mild stroke patients. Conclusion: Further investigation may be needed to illustrate the effects of improving nutritional status on stroke patients.

Reduction in Severity of All-Cause Gastroenteritis Requiring Hospitalisation in Children Vaccinated against Rotavirus in Malawi

Rotavirus is the major cause of severe gastroenteritis in children aged <5 years. Introduction of the G1P[8] Rotarix® rotavirus vaccine in Malawi in 2012 has reduced rotavirus-associated hospitalisations and diarrhoeal mortality. However, the impact of rotavirus vaccine on the severity of gastroenteritis presented in children requiring hospitalisation remains unknown. We conducted a hospital-based surveillance study to assess the impact of Rotarix® vaccination on the severity of gastroenteritis presented by Malawian children. Stool samples were collected from children aged <5 years who required hospitalisation with acute gastroenteritis from December 2011 to October 2019. Gastroenteritis severity was determined using Ruuska and Vesikari scores. Rotavirus was detected using enzyme immunoassay. Rotavirus genotypes were determined using nested RT-PCR. Associations between Rotarix® vaccination and gastroenteritis severity were investigated using adjusted linear regression. In total, 3159 children were enrolled. After adjusting for mid-upper arm circumference (MUAC), age, gender and receipt of other vaccines, all-cause gastroenteritis severity scores were 2.21 units lower (p < 0.001) among Rotarix®-vaccinated (n = 2224) compared to Rotarix®-unvaccinated children (n = 935). The reduction in severity score was observed against every rotavirus genotype, although the magnitude was smaller among those infected with G12P[6] compared to the remaining genotypes (p = 0.011). Each one-year increment in age was associated with a decrease of 0.43 severity score (p < 0.001). Our findings provide additional evidence on the impact of Rotarix® in Malawi, lending further support to Malawi’s Rotarix® programme.

Mid-Upper Arm Circumference as an Indicator of Quality of Life of Patients with Advanced Cancer

Purpose Mid-upper arm circumference (MUAC) has been used to assess malnutrition and health status across various disease groups. However, it is unclear whether MUAC is associated with quality of life (QOL) of patients with advanced cancer. Our goal was to investigate the relationship between MUAC and QOL in ambulatory out-patients with advanced cancer. Method This was a cross-sectional study conducted in a tertiary cancer center in South Korea. A total of 200 patients with advanced cancer at oncology clinics of Seoul National University Bundang Hospital from March 2016 to January 2019 were enrolled. Out-patients with advanced cancer whose survival was expected to be less than one year by their oncologists were enrolled. QOL of patients was evaluated using the European Organization for Research and Treatment of Cancer quality of life questionnaire core 30 (EORTC QLQ-C30). Associations of QOL with MUAC and nutritional parameters were examined with generalized linear models. Results The most common cancer sites were the lung, colon or rectum, and genitourinary tract. In univariate analyses, significant factors associated with higher summary score of EORTC QLQ-C30 were higher MUAC (≥ 26.5 cm, p < 0.001), higher body mass index (BMI) (≥ 22 kg/m2, p < 0.001), higher serum albumin (≥ 3.7 g/dL, p = 0.004), higher creatinine (≥ 0.8 mg/dL, p = 0.023), and higher uric acid (≥ 5 mg/dL, p = 0.001). In multivariate analysis, higher serum albumin (≥ 3.7 g/dL, p < 0.01) and higher MUAC (≥ 26.5 cm, p = 0.03) were independently associated with better summary score of EORTC QLQ-C-30. Conclusion MUAC was highly associated with QOL in terms of summary score and overall health status. Thus, MUAC, with its simplicity, can be a useful tool to reflect QOL in patients with advanced cancer.

The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese

In order to explore the association between trajectories of body mass index (BMI) and mid-upper arm circumference (MUAC) and diabetes and to assess the effectiveness of the models to predict diabetes among Chinese prediabetic people, we conducted this study. Using a national longitudinal study, 1529 cases were involved for analyzing the association between diabetes and BMI trajectories or MUAC trajectories. Growth mixture modeling was conducted among the prediabetic Chinese population to explore the trajectories of BMI and MUAC, and logistic regression was applied to evaluate the association between these trajectories and the risk of diabetes. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were applied to assess the feasibility of prediction. BMI and MUAC were categorized into 4-class trajectories, respectively. Statistically significant associations were observed between diabetes in certain BMI and MUAC trajectories. The AUC for trajectories of BMI and MUAC to predict diabetes was 0.752 (95% CI: 0.690–0.814). A simple cross-validation using logistic regression indicated an acceptable efficiency of the prediction. Diabetes prevention programs should emphasize the significance of body weight control and maintaining skeletal muscle mass and resistance training should be recommended for prediabetes.

Mid-upper arm circumference for identifying adult overweight in large-scale population-based surveys: empirical evaluation using data of the EAT Addis study, Ethiopia

ObjectivesThe present study evaluates body circumferences as a nutrition screening tool for women of reproductive age with children less than 5 years of age to improve the detection of overweight and obesity in a community setting.DesignThis study draws data from a community-based cross-sectional study conducted between July–August 2017 and January–February 2018 to account for seasonality in Addis Ababa, Ethiopia.SettingOne hundred and sixteen districts were included in Addis Ababa, Ethiopia.ParticipantsA total of 4914 women of reproductive age with children less than 5 years of age were participated in this study.Primary and secondary outcome measuresPrimary outcome measures included anthropometric indices. There were no secondary outcomes.ResultsThe optimal cut-off points to identify overweight women of reproductive age were >87.5 cm for waist circumference (WC), >31.7 cm for neck circumference (NC) and >28.0 cm for mid-upper arm circumference (MUAC) based on the highest corresponding Youden index. The area under the receiver operating characteristics curve was 0.92 (95% CI: 0.91 to 0.93) for WC, 0.83 (95% CI: 0.82 to 0.84) for NC and 0.91 (95% CI: 0.89 to 0.92) for MUAC.ConclusionsOur result shows that WC and MUAC are alternative tools to body mass index. Both WC and MUAC are effective in identifying overweight women. We recommend using MUAC in large-scale population-based assessments to identify overweight and obesity in low-income settings as it is logistically simpler and operationally feasible.